{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:19:31Z","timestamp":1760242771474,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2016,7,7]],"date-time":"2016-07-07T00:00:00Z","timestamp":1467849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["61371135"],"award-info":[{"award-number":["61371135"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Beihang University Innovation &amp; Practice Fund for Graduate","award":["YCSJ-02-2015-07"],"award-info":[{"award-number":["YCSJ-02-2015-07"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Precise localization has attracted considerable interest in Wireless Sensor Networks (WSNs) localization systems. Due to the internal or external disturbance, the existence of the outliers, including both the distance outliers and the anchor outliers, severely decreases the localization accuracy. In order to eliminate both kinds of outliers simultaneously, an outlier detection method is proposed based on the maximum entropy principle and fuzzy set theory. Since not all the outliers can be detected in the detection process, the Maximum Entropy Function (MEF) method is utilized to tolerate the errors and calculate the optimal estimated locations of unknown nodes. Simulation results demonstrate that the proposed localization method remains stable while the outliers vary. Moreover, the localization accuracy is highly improved by wisely rejecting outliers.<\/jats:p>","DOI":"10.3390\/s16071041","type":"journal-article","created":{"date-parts":[[2016,7,7]],"date-time":"2016-07-07T09:49:06Z","timestamp":1467884946000},"page":"1041","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["An MEF-Based Localization Algorithm against Outliers in Wireless Sensor Networks"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8729-8847","authenticated-orcid":false,"given":"Dandan","family":"Wang","sequence":"first","affiliation":[{"name":"School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Xueyuan Road No.37, Haidian District, Beijing 100191, China"}]},{"given":"Jiangwen","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Xueyuan Road No.37, Haidian District, Beijing 100191, China"}]},{"given":"Meimei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Xueyuan Road No.37, Haidian District, Beijing 100191, China"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Xueyuan Road No.37, Haidian District, Beijing 100191, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18410","DOI":"10.3390\/s141018410","article-title":"Distributed RSS-based localization in wireless sensor networks based on Second-order cone programming","volume":"14","author":"Tomic","year":"2014","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/LSP.2015.2505138","article-title":"A sample and accurate TDOA-AOA localization method using two stations","volume":"23","author":"Yin","year":"2016","journal-title":"IEEE Signal Process. 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